中国县域生态资产损益的影响机制及优化提升路径

doi:10.11821/dlxb202205015

地理学报 ›› 2022, Vol. 77 ›› Issue (5): 1260-1274.doi: 10.11821/dlxb202205015

中国县域生态资产损益的影响机制及优化提升路径

李佳慧¹^,²(), 黄麟¹(), 曹巍¹

1.中国科学院地理科学与资源研究所中国科学院陆地表层格局与模拟重点实验室,北京 100101
2.中国科学院大学,北京 100049

收稿日期:2021-06-23 修回日期:2022-01-01 出版日期:2022-05-25 发布日期:2022-07-25
通讯作者: 黄麟(1981-), 女, 四川宜宾人, 博士, 副研究员, 研究方向为土地利用变化的生态/气候效应、生态系统综合评估。E-mail: huanglin@igsnrr.ac.cn
作者简介:李佳慧(1997-), 女, 湖南怀化人, 硕士生, 主要从事生态环境遥感与信息系统研究。E-mail: lijh.19s@igsnrr.ac.cn
基金资助:
美丽中国生态文明建设科技工程专项(XDA23020202)

The influencing mechanism of ecological asset gains and losses at the county level in China and its optimization and promotion paths

LI Jiahui¹^,²(), HUANG Lin¹(), CAO Wei¹

1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
2. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2021-06-23 Revised:2022-01-01 Published:2022-05-25 Online:2022-07-25
Supported by:
The Strategic Priority Research Program of the Chinese Academy of Sciences(XDA23020202)

摘要/Abstract

摘要：

生态资源资产化、生态资产资本化是实现“两山”转化的一个重要途径,开展生态资产及其损益核算有助于生态系统的有效保护、科学管理和可持续利用。本文在借鉴国内外生态资产相关研究的基础上,构建了县域尺度生态资产及其损益核算技术体系,分析了1990—2018年中国县域生态资产的时空变化特征,明晰了造成生态资产损益的影响因素及作用机制,并针对具有不同生态资源类型、损益状况、驱动要素特征的县域提出了差异化的优化提升路径。结果表明：① 以农田、森林生态资源为主的县域数分别约占县域总数的45%和37%;1990—2018年中国县域生态存量资产的质量整体呈波动中上升趋势,而生态流量资产的变化趋势差异显著,近70%县域水源涵养量减少。② 生态流量资产价值呈现损与益态势的县域数分别约占44%和37%,空间分布呈现与“胡焕庸线”一致的分割特征,即西北广大地区县域明显增益,而东部和南部县域有所减损。③ 1990—2018年中国超过70%县域生态资产变化受气候变化与人类活动共同驱动,人类活动对生态资产增益县域的平均作用率约80%,而气候变化对生态资产减损县域的平均作用率约为60%。④ 综合分析,可将全国县域分为适应、减缓气候变化和生态资源修复、保护、管理5种类型,采用差异化的生态资产优化提升路径。

关键词: 生态资产, 损益状况, 气候变化, 人类活动, 提升路径

Abstract:

The capitalization of ecological resources and ecological asset is an important way to realize the transformation to "Lucid Waters and Lush Mountains are Invaluable Assets". The accounting of ecological asset and its gains and losses is conducive to the effective protection, scientific management and sustainable utilization of the ecosystem. Based on relevant domestic and foreign research on ecological asset, this paper developed a technical accounting system of ecological asset and its gains and losses at the county level, analyzed the spatial and temporal variations of ecological asset in China from 1990 to 2018, and then identified the influencing factors which caused the gains and losses of ecological asset. The optimization and promotion paths were finally proposed for counties with different types of ecological resources, gain and loss status and varied driving factors. The results showed that about 45% and 37% of counties were dominated by farmland and forest ecological resources, respectively. From 1990 to 2018, the quality of county-level ecological stock asset showed an increasing trend with fluctuation, while the change trend of ecological flow asset was significantly different, showing decreased water conservation volume in nearly 70% of the counties. The number of counties with the gains and losses of ecological flow asset accounted for approximately 44% and 37%, respectively. The spatial distribution of the gains and losses of ecological flow asset showed the same segmentation characteristics as "Hu Line", that is, the counties in the vastness of northwest China experienced significant gains, while decreases were widespread in eastern and southern China. Over the study period, the change of ecological asset in more than 70% of the counties in China was driven by climate change and human activities. The average impact degree of human activities affecting the gains of ecological asset in counties was about 80%, while that of climate change affecting the losses of ecological asset in counties was about 60%. Through comprehensive analyses, counties in China can be classified into five types, which consist of climate change mitigation, climate change adaptation, ecological resources restoration, ecological resources protection, and ecological resources management. And differentiated optimization and promotion paths can be adopted to achieve the gains of ecological asset.

Key words: ecological asset, gains and losses, climate change, human activities, optimization and promotion paths

李佳慧, 黄麟, 曹巍. 中国县域生态资产损益的影响机制及优化提升路径[J]. 地理学报, 2022, 77(5): 1260-1274.

LI Jiahui, HUANG Lin, CAO Wei. The influencing mechanism of ecological asset gains and losses at the county level in China and its optimization and promotion paths[J]. Acta Geographica Sinica, 2022, 77(5): 1260-1274.

图/表 9

表1

县域生态资产核算评估指标与方法

资产类别	一级指标	二级指标	核算方法	指标及参数说明
存量资产	生态资源资产面积	资产类型	生态资源类型面积占比的组合排序	Ⅰ类：农田类、农林湿类、农林草类、农林类、农草类、农湿类 Ⅱ类：森林类、林农草类、林农类、林草类 Ⅲ类：草地类、草农类、草林类、草荒类 Ⅳ类：荒漠类 Ⅴ类：其他类
存量资产	生态资源资产质量	质量指数	$E Q i j = N P P i j M N P P i$ $E A Q I k = ∑ i = 1 m E Q i j S k i × S k i S k$	$E Q i j$ 是i类生态资产j栅格的生态资产质量指数; $M N P P i$ 是全国i类生态资产质量最高的栅格值; $E A Q I k$ 是k县域的生态资产质量指数; $S k i$ 是k县域i类生态资产的面积; $S k$ 是k县域生态资产的总面积。
流量资产	供给服务	食物供给	$V F S = F S × P f$	$F S$ 为粮食产量(t); $P f$ 为单价,稻谷、小麦与玉米3种粮食作物平均售价为2194元·t^-1。
	供给服务	生产原材料供给	$V P S = ∑ j = 1 m P S j × P p j$	$P S j$ 为j产品产量(t); $P p j$ 为单价,棉花与油料作物平均售价分别为14564元·t^-1与6452元·t^-1。
	调节服务	减少泥沙淤积	$S C = (M s c - M s c e) × A$ $V S C = S C / ρ s × P S C$	$S C$ 为土壤保持量(t); $M s c$ 为实际地表覆盖条件下土壤水蚀量(t·hm^-2·a^-1); $M s c e$ 为极度退化状态下土壤水蚀量(t·hm^-2·a^-1); $A$ 为生态系统面积(hm²); $ρ s$ 为土壤容重(t·m^-3)^[33]; $P S C$ 为挖取单位体积土方费,取12.6元·m^{-3 [34]}。
		减少沙尘污染	$S F = (M s f - M s f e) × A$ $V S F = S F × P S F$	$S F$ 为防风固沙量(t); $M s f$ 为实际地表覆盖条件下土壤风蚀量(t·hm^-2·a^-1); $M s f e$ 为极度退化状态下土壤风蚀量(t·hm^-2·a^-1); $A$ 为生态系统面积(hm²); $P S F$ 为治沙成本,取150元·t^{-1 [34]}。
		减少土壤肥力损失	$V N R = ∑ i = 1 m (S C + S F) × C i × T i × P c i$	$C i$ 为土壤氮、磷、钾、有机质的含量(%), $T i$ 为氮、磷、钾折算为尿素、过磷酸钙和氯化钾的系数,分别为2.164、4.065、1.923^[35]; $P c i$ 为尿素、过磷酸钙、氯化钾和有机肥的市场价格,分别为1990元·t^-1、800元·t^-1、2200元·t^-1和320元·t^{-1 [34]}。
		水量调节	$W C = A × (J 0 × K) × (R 0 - R r)$ $V W R = W C × P W R$	$W C$ 为拦蓄降水量(t·a^-1); $A$ 为生态系统面积(hm²); $J 0$ 为年降水量(mm); $K$ 为产流降水量占降水总量的比例; $R 0$ 为产流降水条件下裸地降水径流率; $R r$ 为产流降水条件下生态系统降水径流率; $P W R$ 为水库单位库容成本,取6.1107元·m^{-3 [34]}。
		水质净化	$V W P = W C × P W P$	$P W P$ 为污水处理价格,取0.95元·t^-1。

表1

表2

生态资产损益的驱动因素判定及作用率计算方法

$s l o p e o b s$	$s l o p e c c$	$s l o p e h a$	气候变化作用率(%)	人类活动作用率(%)	说明
> 0	> 0	> 0	$s l o p e c c s l o p e o b s$	$s l o p e h a s l o p e o b s$	气候变化和人类活动共同作用导致生态资产增益
	> 0	< 0	100	0	气候变化导致生态资产增益
	< 0	> 0	0	100	人类活动导致生态资产增益
< 0	< 0	< 0	$s l o p e c c s l o p e o b s$	$s l o p e h a s l o p e o b s$	气候变化和人类活动共同作用导致生态资产减损
	< 0	> 0	100	0	气候变化导致生态资产减损
	> 0	< 0	0	100	人类活动导致生态资产减损

表2

表3

图1

图2

图3

图4

图5

图6

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类型名称	类型组成	描述
气候变化适应型	ⅠAb、ⅡAb、ⅢAb、ⅣAb、ⅠCb、ⅡCb、ⅢCb	以农田、森林与草地资产类型为主,且主要由气候变化驱动作用导致生态资产持衡或提升的县域
气候变化减缓型	ⅠBb、ⅡBb、ⅢBb、ⅣBb	以农田、森林资产类型为主,且主要由气候变化驱动作用导致生态资产减损的县域
生态资源修复型	ⅠBa、ⅡBa、ⅢBa、ⅣBa	以农田、森林资产类型为主,且主要由人类活动驱动作用导致生态资产减损的县域
生态资源保护型	ⅠAa、ⅡAa、ⅢAa、ⅣAa	以农田、森林、草地资产类型为主,且主要由人类活动驱动作用导致生态资产提升的县域
生态资源管理型	ⅠCa、ⅡCa、ⅢCa	以农田与森林资产类型为主,且主要在人类活动影响下生态资产持衡的县域

中国县域生态资产损益的影响机制及优化提升路径

The influencing mechanism of ecological asset gains and losses at the county level in China and its optimization and promotion paths

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